from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


_SCREAMING_SNAKE_CASE 		=      logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE 		=      {
    """microsoft/table-transformer-detection""": (
        """https://huggingface.co/microsoft/table-transformer-detection/resolve/main/config.json"""
    ),
}
class SCREAMING_SNAKE_CASE_		(      __lowerCAmelCase		):
   __lowerCAmelCase           =				"""table-transformer"""
   __lowerCAmelCase           =				["""past_key_values"""]
   __lowerCAmelCase           =				{
       """hidden_size""": """d_model""",
       """num_attention_heads""": """encoder_attention_heads""",
   }







   def __init__(     self						:						Dict   ,   lowerCamelCase_						:						Dict=True   ,   lowerCamelCase_						:						Union[str, Any]=None   ,   lowerCamelCase_						:						List[Any]=3   ,   lowerCamelCase_						:						List[str]=100   ,   lowerCamelCase_						:						Optional[Any]=6   ,   lowerCamelCase_						:						Optional[int]=2048   ,   lowerCamelCase_						:						Optional[Any]=8   ,   lowerCamelCase_						:						int=6   ,   lowerCamelCase_						:						Optional[Any]=2048   ,   lowerCamelCase_						:						List[Any]=8   ,   lowerCamelCase_						:						Optional[Any]=0.0   ,   lowerCamelCase_						:						List[str]=0.0   ,   lowerCamelCase_						:						Union[str, Any]=True   ,   lowerCamelCase_						:						Optional[Any]="relu"   ,   lowerCamelCase_						:						List[str]=256   ,   lowerCamelCase_						:						Optional[int]=0.1   ,   lowerCamelCase_						:						int=0.0   ,   lowerCamelCase_						:						str=0.0   ,   lowerCamelCase_						:						Optional[Any]=0.0_2   ,   lowerCamelCase_						:						Tuple=1.0   ,   lowerCamelCase_						:						Union[str, Any]=False   ,   lowerCamelCase_						:						int="sine"   ,   lowerCamelCase_						:						Union[str, Any]="resnet50"   ,   lowerCamelCase_						:						Optional[int]=True   ,   lowerCamelCase_						:						Any=False   ,   lowerCamelCase_						:						List[str]=1   ,   lowerCamelCase_						:						List[str]=5   ,   lowerCamelCase_						:						Any=2   ,   lowerCamelCase_						:						Union[str, Any]=1   ,   lowerCamelCase_						:						Optional[int]=1   ,   lowerCamelCase_						:						Optional[Any]=5   ,   lowerCamelCase_						:						Tuple=2   ,   lowerCamelCase_						:						Any=0.1   ,   **lowerCamelCase_						:						Any   ,   ):





    """simple docstring"""


    if backbone_config is not None and use_timm_backbone:
     raise ValueError("""You can't specify both `backbone_config` and `use_timm_backbone`."""				)

    if not use_timm_backbone:
     if backbone_config is None:
      logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""				)
      UpperCamelCase			  =      CONFIG_MAPPING["""resnet"""](out_features=["""stage4"""]				)
     elif isinstance(lowerCamelCase_   ,   lowerCamelCase_				):
      UpperCamelCase			  =      backbone_config.get("""model_type"""				)
      UpperCamelCase			  =      CONFIG_MAPPING[backbone_model_type]
      UpperCamelCase			  =      config_class.from_dict(lowerCamelCase_				)
     # set timm attributes to None
     UpperCamelCase  ,     UpperCamelCase  ,     UpperCamelCase			  =      None, None, None

    UpperCamelCase			  =      use_timm_backbone
    UpperCamelCase			  =      backbone_config
    UpperCamelCase			  =      num_channels
    UpperCamelCase			  =      num_queries
    UpperCamelCase			  =      d_model
    UpperCamelCase			  =      encoder_ffn_dim
    UpperCamelCase			  =      encoder_layers
    UpperCamelCase			  =      encoder_attention_heads
    UpperCamelCase			  =      decoder_ffn_dim
    UpperCamelCase			  =      decoder_layers
    UpperCamelCase			  =      decoder_attention_heads
    UpperCamelCase			  =      dropout
    UpperCamelCase			  =      attention_dropout
    UpperCamelCase			  =      activation_dropout
    UpperCamelCase			  =      activation_function
    UpperCamelCase			  =      init_std
    UpperCamelCase			  =      init_xavier_std
    UpperCamelCase			  =      encoder_layerdrop
    UpperCamelCase			  =      decoder_layerdrop
    UpperCamelCase			  =      encoder_layers
    UpperCamelCase			  =      auxiliary_loss
    UpperCamelCase			  =      position_embedding_type
    UpperCamelCase			  =      backbone
    UpperCamelCase			  =      use_pretrained_backbone
    UpperCamelCase			  =      dilation
    # Hungarian matcher
    UpperCamelCase			  =      class_cost
    UpperCamelCase			  =      bbox_cost
    UpperCamelCase			  =      giou_cost
    # Loss coefficients
    UpperCamelCase			  =      mask_loss_coefficient
    UpperCamelCase			  =      dice_loss_coefficient
    UpperCamelCase			  =      bbox_loss_coefficient
    UpperCamelCase			  =      giou_loss_coefficient
    UpperCamelCase			  =      eos_coefficient
    super().__init__(is_encoder_decoder=lowerCamelCase_   ,   **lowerCamelCase_				)







   @property
   def 						lowerCamelCase_	(     self						:						Dict				):





    """simple docstring"""


    return self.encoder_attention_heads







   @property
   def 						lowerCamelCase_	(     self						:						Any				):





    """simple docstring"""


    return self.d_model





class SCREAMING_SNAKE_CASE_		(      __lowerCAmelCase		):
   __lowerCAmelCase           =				version.parse("""1.11"""		)







   @property
   def 						lowerCamelCase_	(     self						:						Union[str, Any]				):





    """simple docstring"""


    return OrderedDict(
        [
            ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
            ("""pixel_mask""", {0: """batch"""}),
        ]				)







   @property
   def 						lowerCamelCase_	(     self						:						List[str]				):





    """simple docstring"""


    return 1E-5







   @property
   def 						lowerCamelCase_	(     self						:						Tuple				):





    """simple docstring"""


    return 12

def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_       )		->	List[str]:







 '''simple docstring'''
 _enforce_args(UpperCamelCase_							,					UpperCamelCase_       )
 if n == 0:
  return 0
 UpperCamelCase			  =      float("""-inf"""       )
 for i in range(1							,					n + 1       ):
  UpperCamelCase			  =      max(
      UpperCamelCase_							,					prices[i - 1] + naive_cut_rod_recursive(n - i							,					UpperCamelCase_       )       )

 return max_revue





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_       )		->	Optional[Any]:







 '''simple docstring'''
 _enforce_args(UpperCamelCase_							,					UpperCamelCase_       )
 UpperCamelCase			  =      [float("""-inf"""       ) for _ in range(n + 1       )]
 return _top_down_cut_rod_recursive(UpperCamelCase_							,					UpperCamelCase_							,					UpperCamelCase_       )





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_							,					UpperCamelCase_       )		->	List[Any]:







 '''simple docstring'''
 if max_rev[n] >= 0:
  return max_rev[n]
 elif n == 0:
  return 0
 else:
  UpperCamelCase			  =      float("""-inf"""       )
  for i in range(1							,					n + 1       ):
   UpperCamelCase			  =      max(
       UpperCamelCase_							,					prices[i - 1] + _top_down_cut_rod_recursive(n - i							,					UpperCamelCase_							,					UpperCamelCase_       )							,					)

  UpperCamelCase			  =      max_revenue

 return max_rev[n]





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_       )		->	Union[str, Any]:







 '''simple docstring'''
 _enforce_args(UpperCamelCase_							,					UpperCamelCase_       )

 # length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
 # length 0.
 UpperCamelCase			  =      [float("""-inf"""       ) for _ in range(n + 1       )]
 UpperCamelCase			  =      0

 for i in range(1							,					n + 1       ):
  UpperCamelCase			  =      max_rev[i]
  for j in range(1							,					i + 1       ):
   UpperCamelCase			  =      max(UpperCamelCase_							,					prices[j - 1] + max_rev[i - j]       )

  UpperCamelCase			  =      max_revenue_i

 return max_rev[n]





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_       )		->	Union[str, Any]:







 '''simple docstring'''
 if n < 0:
  UpperCamelCase			  =      f"""n must be greater than or equal to 0. Got n = {n}"""
  raise ValueError(UpperCamelCase_       )

 if n > len(UpperCamelCase_       ):
  UpperCamelCase			  =      (
      """Each integral piece of rod must have a corresponding price. """
      f"""Got n = {n} but length of prices = {len(UpperCamelCase_       )}"""
  )
  raise ValueError(UpperCamelCase_       )





def 			lowercase(	)		->	str:







 '''simple docstring'''
 UpperCamelCase			  =      [6, 10, 12, 15, 20, 23]
 UpperCamelCase			  =      len(UpperCamelCase_       )

 # the best revenue comes from cutting the rod into 6 pieces, each
 # of length 1 resulting in a revenue of 6 * 6 = 36.
 UpperCamelCase			  =      36

 UpperCamelCase			  =      top_down_cut_rod(UpperCamelCase_							,					UpperCamelCase_       )
 UpperCamelCase			  =      bottom_up_cut_rod(UpperCamelCase_							,					UpperCamelCase_       )
 UpperCamelCase			  =      naive_cut_rod_recursive(UpperCamelCase_							,					UpperCamelCase_       )

 assert expected_max_revenue == max_rev_top_down
 assert max_rev_top_down == max_rev_bottom_up
 assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
     main()
